The arrival of 100K+ GPU clusters marks a new frontier in AI infrastructure. Standard communication stack meets new challenges as physical topologies span multiple datacenter buildings, introducing high bandwidth-delay product links where latency increases by up to 30× compared to intra-rack traffic. Furthermore, the transition toward Mixture-of-Experts architectures generating bursty all-to-all patterns that create transient congestion hotspots. These constraints, combined with an operational environment where hardware failures shift from anomalies to frequent occurrences, renders traditionally lightweight operations like initialization and resource management challenging.

Modern "self-driving'' service infrastructures consist of a diverse collection of distributed control components providing a broad spectrum of application- and network-centric functions. The complex and non-deterministic nature of these interactions leads to failures, ranging from subtle gray failures to catastrophic service outages, that are difficult to anticipate and repair.